WLreg: A new re-parametrization of the Weighted Lindley distribution and its regression model
A novel re-parametrization of the weighted Lindley distribution is introduced to develop a regression model suitable for skewed dependent variables defined on [Formula: see text]. This new model is called the WL2 regression model. It is shown to outperform existing models such as the gamma, extended gamma, and Maxwell-Boltzmann-exponential regression models. Parameter estimation is performed using the maximum likelihood estimation technique, and the efficiency of these estimates is assessed through a simulation study. An application to a house price data set is presented to highlight the importance of the WL2 regression model. In addition, we propose the WLreg software, accessible via https://bartinuni.shinyapps.io/WLreg, to facilitate the application of the new regression model for practitioners in the field.
Authors
- Hana Nasser Alqifari (ORCID: https://orcid.org/0000-0002-7577-6079)
- Emrah Altun (ORCID: https://orcid.org/0000-0001-5065-2523)
- Christophe Chesneau (ORCID: https://orcid.org/0000-0002-1522-9292)
Institutions
- Qassim University (SA)
- Bartin University (TR)
- Normandie Université (FR)
- Université de Caen Normandie (FR)
Publication Details
- Journal
- PLoS ONE
- Published
- 2025-06-09
- DOI
- https://doi.org/10.1371/journal.pone.0324005
- Primary Topic
- Statistical Distribution Estimation and Applications
- Type
- article
- Field-Weighted Citation Impact
- 0.00